





"""simple docstring"""





import time
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device

from ..test_modeling_common import ids_tensor


if is_torch_available():
       import torch

       from transformers.generation import (
           MaxLengthCriteria,
           MaxNewTokensCriteria,
           MaxTimeCriteria,
           StoppingCriteriaList,
           validate_stopping_criteria,
       )

@require_torch
class 						lowercase   (   unittest.TestCase   ):





      def        _snake_case     (			self ,		lowercase					)						->	Optional[Any]:
            lowerCAmelCase    		=			3
            lowerCAmelCase    		=			250

            lowerCAmelCase    		=			ids_tensor((batch_size, length) ,		lowercase					)
            lowerCAmelCase    		=			torch.ones((batch_size, length) ,		device=lowercase ,		dtype=torch.float					) / length
            return input_ids, scores





      def        _snake_case     (			self					)						->	Any:
            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(5					)

            lowerCAmelCase    		=			StoppingCriteriaList(
                [
                    MaxLengthCriteria(max_length=10					),
                    MaxTimeCriteria(max_time=0.1					),
                ]					)

            self.assertFalse(criteria(lowercase ,		lowercase					)					)

            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(9					)
            self.assertFalse(criteria(lowercase ,		lowercase					)					)

            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(10					)
            self.assertTrue(criteria(lowercase ,		lowercase					)					)





      def        _snake_case     (			self					)						->	Union[str, Any]:
            lowerCAmelCase    		=			MaxLengthCriteria(max_length=10					)

            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(5					)
            self.assertFalse(criteria(lowercase ,		lowercase					)					)

            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(9					)
            self.assertFalse(criteria(lowercase ,		lowercase					)					)

            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(10					)
            self.assertTrue(criteria(lowercase ,		lowercase					)					)





      def        _snake_case     (			self					)						->	int:
            lowerCAmelCase    		=			MaxNewTokensCriteria(start_length=5 ,		max_new_tokens=5					)

            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(5					)
            self.assertFalse(criteria(lowercase ,		lowercase					)					)

            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(9					)
            self.assertFalse(criteria(lowercase ,		lowercase					)					)

            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(10					)
            self.assertTrue(criteria(lowercase ,		lowercase					)					)

            lowerCAmelCase    		=			StoppingCriteriaList([criteria]					)
            self.assertEqual(criteria_list.max_length ,		10					)





      def        _snake_case     (			self					)						->	Any:
            lowerCAmelCase		,						lowerCAmelCase    		=			self._get_tensors(5					)

            lowerCAmelCase    		=			MaxTimeCriteria(max_time=0.1					)
            self.assertFalse(criteria(lowercase ,		lowercase					)					)

            lowerCAmelCase    		=			MaxTimeCriteria(max_time=0.1 ,		initial_timestamp=time.time() - 0.2					)
            self.assertTrue(criteria(lowercase ,		lowercase					)					)





      def        _snake_case     (			self					)						->	int:
            validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10					)]					) ,		10					)

            with self.assertWarns(lowercase					):
                  validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10					)]					) ,		11					)

            lowerCAmelCase    		=			validate_stopping_criteria(StoppingCriteriaList() ,		11					)

            self.assertEqual(len(lowercase					) ,		1					)













"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__   =  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   =  {
    "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
    "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/config.json"
    # See all FNet models at https://huggingface.co/models?filter=fnet
}

class 						lowercase   (   _UpperCAmelCase   ):
      _SCREAMING_SNAKE_CASE							      = 'fnet'





      def __init__(			self ,		lowercase=32_000 ,		lowercase=768 ,		lowercase=12 ,		lowercase=3_072 ,		lowercase="gelu_new" ,		lowercase=0.1 ,		lowercase=512 ,		lowercase=4 ,		lowercase=0.02 ,		lowercase=1e-12 ,		lowercase=False ,		lowercase=512 ,		lowercase=3 ,		lowercase=1 ,		lowercase=2 ,		**lowercase ,		)						->	int:
            super().__init__(pad_token_id=lowercase ,		bos_token_id=lowercase ,		eos_token_id=lowercase ,		**lowercase					)

            lowerCAmelCase    		=			vocab_size
            lowerCAmelCase    		=			max_position_embeddings
            lowerCAmelCase    		=			hidden_size
            lowerCAmelCase    		=			num_hidden_layers
            lowerCAmelCase    		=			intermediate_size
            lowerCAmelCase    		=			hidden_act
            lowerCAmelCase    		=			hidden_dropout_prob
            lowerCAmelCase    		=			initializer_range
            lowerCAmelCase    		=			type_vocab_size
            lowerCAmelCase    		=			layer_norm_eps
            lowerCAmelCase    		=			use_tpu_fourier_optimizations
            lowerCAmelCase    		=			tpu_short_seq_length






